Abstract

This paper is devoted to studying the capabilities of modern neural networks in image processing for solving the problem of monitoring the state of steel and reinforced concrete structures. The article presents a method for solving monitoring problems based on the use of a combination of several neural networks focused on recognizing a fragment of a structure and parts of a structure. Methods for training neural networks on small training samples are proposed. The results of the operation of the algorithms on real images are presented, showing the consistency and efficiency of the proposed solution.

中文翻译：

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使用机器学习技术检测金属结构图像中的缺陷

摘要

本文致力于研究现代神经网络在图像处理方面的能力，以解决监测钢结构和钢筋混凝土结构状态的问题。本文提出了一种解决监控问题的方法，该方法基于多个神经网络的组合使用，重点是识别结构的片段和结构的部分。提出了在小训练样本上训练神经网络的方法。给出了算法在真实图像上的操作结果，显示了所提出的解决方案的一致性和效率。